http://fs.unm.edu/IJMC/CharacterizationOfLocallyDuallyFlat.pdf WebJan 1, 2008 · Information geometry emerged from studies on invariant properties of a manifold of probability distributions. It includes convex analysis and its duality as a …
Simple question on parallel transport in dually flat manifolds
WebFeb 2, 2016 · As an important special case, we study a dually flat Riemannian manifold. It may be regarded as a dualistic extension of the Euclidean space. The generalized … WebAbout Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How YouTube works Test new features Press Copyright Contact us Creators ... mod minecraft france 1.16.5
Dually flat and projectively flat Minkowskian product
WebMar 20, 2024 · Exponential families and mixture families are parametric probability models that can be geometrically studied as smooth statistical manifolds with respect to any statistical divergence like the Kullback-Leibler (KL) divergence or the Hellinger divergence. When equipping a statistical manifold with the KL divergence, the induced manifold … In mathematics, a Riemannian manifold is said to be flat if its Riemann curvature tensor is everywhere zero. Intuitively, a flat manifold is one that "locally looks like" Euclidean space in terms of distances and angles, e.g. the interior angles of a triangle add up to 180°. The universal cover of a complete flat manifold is Euclidean space. This can be used to prove the theorem of Bieberbach (1911, 1912) that all compact flat manifolds are finitely covered by tori; th… However, they satisfy a generalization of the Pythagorean theorem, and in information geometry the corresponding statistical manifold is interpreted as a (dually) flat manifold. This allows many techniques of optimization theory to be generalized to Bregman divergences, geometrically as … See more In mathematics, specifically statistics and information geometry, a Bregman divergence or Bregman distance is a measure of difference between two points, defined in terms of a strictly convex function; … See more Let $${\displaystyle F:\Omega \to \mathbb {R} }$$ be a continuously-differentiable, strictly convex function defined on a convex set $${\displaystyle \Omega }$$. The Bregman distance associated with F for points $${\displaystyle p,q\in \Omega }$$ is … See more Bregman divergences can be interpreted as limit cases of skewed Jensen divergences (see Nielsen and Boltz, 2011). Jensen … See more In machine learning, Bregman divergences are used to calculate the bi-tempered logistic loss, performing better than the softmax function with noisy datasets. See more • Non-negativity: $${\displaystyle D_{F}(p,q)\geq 0}$$ for all $${\displaystyle p}$$, $${\displaystyle q}$$. This is a consequence of the convexity of $${\displaystyle F}$$ See more A key tool in computational geometry is the idea of projective duality, which maps points to hyperplanes and vice versa, while preserving incidence and above-below relationships. … See more Bregman divergences can also be defined between matrices, between functions, and between measures (distributions). Bregman … See more mod minecraft free download xbox 1